Dixon Mastering .NET Machine Learning

Use machine learning in your .NET applications
1. Auflage 2025
ISBN: 978-1-78588-119-0
Verlag: De Gruyter
Format: PDF
Kopierschutz: Adobe DRM (»Systemvoraussetzungen)

E-Book, Englisch, 358 Seiten

No detailed description available for "Mastering.NET Machine Learning".

Autoren/Hrsg.

Dixon, Jamie

Fachgebiete

• Mathematik | Informatik EDV | Informatik Daten / Datenbanken

Über Autor(innen)

Dixon Jamie :

Jamie Dixon has been writing code for as long as he can remember and has been getting paid to do it since 1995. He was using C# and JavaScript almost exclusively until discovering F#, and now combines all three languages for the problem at hand. He has a passion for discovering overlooked gems in datasets and merging software engineering techniques to scientific computing. When he codes for fun, he spends his time using Phidgets, Netduinos, and Raspberry Pis or spending time in Kaggle competitions using F# or R. Jamie is a bachelor of science in computer science and has been an F# MVP since 2014. He is the former chair of his town's Information Services Advisory Board and is an outspoken advocate of open data. He is also involved with his local.NET User Group (TRINUG) with an emphasis on data analytics, machine learning, and the Internet of Things (IoT). Jamie lives in Cary, North Carolina with his wonderful wife Jill and their three awesome children: Sonoma, Sawyer, and Sloan. He blogs weekly at jamessdixon.wordpress.com and can be found on Twitter at @jamie_dixon.